Real-time signal validation method and system

ABSTRACT

Systems and methods for real-time signal validation are disclosed. In an example embodiment, a subset of terminals in a peer group of satellite terminals is determined. Operational statistics of the satellite terminals in the subset of terminals is measured. Operational statistics of each of the satellite terminals in the subset of terminals is compared to a prior measurement of the same operational statistics. An offset between a current measurement of the operational statistics and the prior measurement of the same operational statistics is determined. An average offset of the current measurement of the operational statistics and the prior measurement of the same operational statistics is determined for the subset of terminals. The average offset for the subset of terminals is merged with a previously determined peer group operational statistic. A signal validation of a terminal is performed using an updated deviation value.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation application that claims priority toand the benefit of U.S. application Ser. No. 13/666,706, filed Nov. 1,2012, the entire content of which is incorporated by reference herein.The present application also relates to the following patentapplications: “Peer Group Diagnosis Detection Method and System,” filedon Jun. 28, 2012, as U.S. patent application Ser. No. 13/536,604,“Problem Signature Terminal Diagnosis Method and System,” filed on Jun.28, 2012, U.S. patent application Ser. No. 13/536,600, and “TerminalDiagnosis Self Correction Method and System,” filed on Jun. 28, 2012,U.S. patent application Ser. No. 13/536,610, the entire contents of eachof which are incorporated by reference herein.

BACKGROUND

Wireless communication systems typically include a plurality of userterminals that are used by customers or end users which transmit andreceive data from satellites and/or other antennas. For a satellitebased communication system, a satellite terminal is typically set up atthe user location by a service technician or installer. For example, auser's home may have a satellite dish installed for receiving internet,telephone, and television service, or the like. The satellite dish isinstalled with associated hardware, such as a transmitter, receiver,modem, router, set-top box, and the like. The service technicianconfigures the terminal for optimal use, for example, by correctlyorienting the satellite dish, configuring all settings appropriately,and testing the terminal to ensure it is working properly before leavingthe installation.

Typically, when a customer of a satellite communication system has aproblem with the service (e.g., service interruption, pixilation, slowinternet), the customer calls a customer service hotline and speaks witha customer service representative. The customer service representativemay attempt to diagnose the problem and determine if any repair isneeded, or determine that the service interruption is caused by weatherconditions or a regional service interruption. Statistical measurementdata from the satellite terminal may be obtained for analysis todetermine if there is a problem. Typically, this measured data mayprovide some insight that may confirm that a problem exists based on thecustomer inquiry. However, this data is generally not as useful fordetecting that a problem exists before the customer notices the problemand places an inquiry call.

SUMMARY

The present disclosure provides a new and innovative method and systemfor real-time signal validation. In an example embodiment, a subset ofterminals in a peer group of satellite terminals is determined. At leastone operational statistic of the satellite terminals in the subset ofterminals is measured. At least one operational statistic of each of thesatellite terminals in the subset of terminals is compared to a priormeasurement of the same at least one operational statistic for each ofthe satellite terminals in the subset of terminals. An offset between acurrent measurement of the at least one operational statistic and theprior measurement of the same at least one operational statistic isdetermined for each of the satellite terminals in the subset ofterminals. An average offset of the current measurement of the at leastone operational statistic and the prior measurement of the same at leastone operational statistic is determined for the subset of terminals. Theaverage offset for the subset of terminals is merged with at least onepreviously determined peer group operational statistic. A signalvalidation of a terminal is performed using an updated deviation value.

Additional features and advantages of the disclosed system, methods, andapparatus are described in, and will be apparent from, the followingDetailed Description and the Figures.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a high level block diagram of an example satellitecommunication system, according to an example embodiment of the presentdisclosure.

FIG. 2 is a high level block diagram of an example communication system,according to an example embodiment of the present disclosure.

FIG. 3 is a detailed block diagram of an example a computing device,according to an example embodiment of the present disclosure.

FIG. 4 is a block diagram of an example peer group diagnosis detectionsystem, according to an example embodiment of the present disclosure.

FIG. 5 includes a flowchart illustrating an example process for peergroup diagnosis detection, according to an example embodiment of thepresent disclosure.

FIG. 6 includes a scatter diagram illustrating an example data set forpeer group diagnosis detection, according to an example embodiment ofthe present disclosure.

FIG. 7 includes a flowchart illustrating an example process forreal-time signal validation, according to an example embodiment of thepresent disclosure.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

A high level block diagram of an example satellite communication system10 is illustrated in FIG. 1. The illustrated system 10 includes asatellite 20 and satellite terminals 30, each including an antenna andassociated hardware (e.g., receiver, transmitter, modem, router,computing device). The satellite terminals 30 may transmit and receivedata to and from the satellite 20. Typically, a satellite 20 receivesdata from a hub terminal 40 which is distributed to many satelliteterminals 30. It should be appreciated that a satellite terminal 30 maycommunicate with one or more satellites 20. Similarly, a satellite 20may communicate with one or more hub terminals 40, and a hub terminal 40may communicate with one or more satellites 20. Typically, a satellite20 communicates with each satellite terminal 30 using an uplink channel51 and a downlink channel 52, and also communicates with a satellite hub40 using a downlink channel 53 and an uplink channel 54. The uplinkchannel 54 and downlink channel 52 may be referred to as a forwardchannel while the uplink channel 51 and downlink channel 53 may bereferred to as a return channel. It should be appreciated that theuplink channels 51, 54 and downlink channels 52, 53 typically eachoperate in different frequency bands and with totally independentcircuitry. Accordingly, for example, a satellite terminal 30 typicallymay transmit data on the uplink channel 51 at a first frequency andreceive data on the downlink channel 52 at a second frequency. For asatellite terminal 30, the performance of the uplink channel 51 and thedownlink channel 52 are typically both separately evaluated indetermining a site diagnosis, as uplink data and downlink data eachprovide insight into any problems which may exist for the satelliteterminal 30.

It should be appreciated that in order for a satellite 20 to communicatewith a satellite terminal 30, the satellite terminal 30 must beconfigured correctly with a proper line of sight to the satellite 20.The satellite communication system 10 may be operating in any broadbandnetwork, for example, the K_(a) band, the K_(u) band, the C band, or thelike. For example, satellite communication system 10 may be implementedon the SPACEWAY® and/or JUPITER™ platform. Accordingly, the system 10may provide satellite coverage over a smaller area or larger area, forexample, regional coverage may be dozens or hundreds of miles wide.Also, for example, the system 10 may provide continental coverage.

If the antenna alignment of the satellite terminal 30 is not within acertain tolerance, transmission and/or reception of data may degradeand/or fail. However, even with proper antenna alignment, a satelliteterminal 30 may have reception or transmission problems due toenvironmental issues such as inclement weather conditions. For example,rain fade is a common problem for certain frequency ranges (e.g., theK_(a) band). Also, other interference sources, such as structures whichmay block a satellite terminal's 30 line of sight, may impedecommunication. Further, problems with terminal components and/orsettings may cause signal degradation or failure. Components may fail ordegrade for a variety of reasons (e.g., physical structural damage,short circuit). In some cases, a particular satellite terminal 30 may beexperiencing multiple different problems simultaneously. Moreover, thereare many potential causes of suboptimal communication for a satelliteterminal 30, and it is often difficult to correctly diagnose thespecific problem or problems a satellite terminal 30 may need corrected.Accordingly, for an operator of a satellite communication system 10, itmay be highly advantageous to improve the accuracy of terminal diagnosiswhen a satellite terminal 30 is experiencing a problem with service.Also, it may be advantageous to detect a problem before a customernotices any interruption or decline in service quality.

It should be appreciated that satellite terminals 30, which may also beknown as user terminals, earth terminals, ground stations, antennasites, or the like, may be referred to in the present application simplyas terminals or sites. Similarly, the terms customer servicerepresentative, customer service agent, and service agent may be usedinterchangeably in the present disclosure. Likewise, installer, servicetechnician, repair technician, onsite technician, installationtechnician, and technician may be used interchangeably in the presentdisclosure. Also, customer, end user, and user may be usedinterchangeably in the present disclosure. Further, it should beappreciated that, the present application may provide exampleembodiments relating to a satellite based communication system 10 asillustrated in FIG. 1, however, the present disclosure may be similarlyapplicable to other wireless communication systems.

A high level block diagram of an example network communications system100 is illustrated in FIG. 2. The illustrated system 100 includes one ormore client devices 102, one or more host devices 104, and one or morecommunication channels 106 (e.g., satellite communication). In asatellite communication system 10, the communication channels 106include communication via the air interface between a hub terminal 40and a satellite 20, and the satellite 20 and a satellite terminal 30.Also, for example, the hub terminal 40 may communicate with a hostdevice 104 (e.g., content provider) and the satellite terminal 30 maycommunicate with a client device 102 (e.g., personal computer).Likewise, a hub terminal 40 and/or satellite terminal 30 may communicatewith devices and/or networks that are not satellite based systems or notwireless (e.g., a local area network).

The system 100 may include a variety of client devices 102, such asdesktop computers, televisions, and the like, which typically include adisplay 112, which is a user display for providing information to users114, and various interface elements as will be discussed in furtherdetail below. A client device 102 may be a mobile device 103, which maybe a laptop computer, a tablet computer, a cellular phone, a personaldigital assistant, etc. The client devices 102 may communicate with thehost device 104 via a connection to one or more communications channels106 such as the Internet or some other data network, including, but notlimited to, any suitable wide area network or local area network. Itshould be appreciated that any of the devices described herein may bedirectly connected to each other instead of over a network. Typically,one or more servers 108 may be part of the network communications system100, and may communicate with host servers 104 and client devices 102.

One host device 104 may interact with a large number of users 114 at aplurality of different client devices 102. Accordingly, each host device104 is typically a high end computer with a large storage capacity, oneor more fast microprocessors, and one or more high speed networkconnections. Conversely, relative to a typical host device 104, eachtypical client device 102 may often include less storage capacity, asingle microprocessor, and a single network connection. It should beappreciated that a user 114 as described herein may include anycustomer, person, or entity which uses the presently disclosed systemand may include a wide variety of parties for both business use andpersonal use.

Typically, host devices 104 and servers 108 store one or more of aplurality of files, programs, databases, and/or web pages in one or morememories for use by the client devices 102, and/or other host devices104 or servers 108. A host device 104 or server 108 may be configuredaccording to its particular operating system, applications, memory,hardware, etc., and may provide various options for managing theexecution of the programs and applications, as well as variousadministrative tasks. A host device 104 or server may interact via oneor more networks with one or more other host devices 104 or servers 108,which may be operated independently. For example, host devices 104 andservers 108 operated by a separate and distinct entities may interacttogether according to some agreed upon protocol.

A detailed block diagram of the electrical systems of an examplecomputing device (e.g., a client device 102, a host device 104) isillustrated in FIG. 3. In this example, the computing device 102, 104includes a main unit 202 which preferably includes one or moreprocessors 204 electrically coupled by an address/data bus 206 to one ormore memory devices 208, other computer circuitry 210, and one or moreinterface circuits 212. The processor 204 may be any suitable processor,such as a microprocessor from the INTEL PENTIUM® family ofmicroprocessors. The memory 208 preferably includes volatile memory andnon-volatile memory. Preferably, the memory 208 stores a softwareprogram that interacts with the other devices in the system 100 asdescribed below. This program may be executed by the processor 204 inany suitable manner. In an example embodiment, memory 208 may be part ofa “cloud” such that cloud computing may be utilized by a computingdevices 102, 104. The memory 208 may also store digital data indicativeof documents, files, programs, web pages, etc. retrieved from acomputing device 102, 104 and/or loaded via an input device 214.

The interface circuit 212 may be implemented using any suitableinterface standard, such as an Ethernet interface and/or a UniversalSerial Bus (USB) interface. One or more input devices 214 may beconnected to the interface circuit 212 for entering data and commandsinto the main unit 202. For example, the input device 214 may be akeyboard, mouse, touch screen, remote control, track pad, track ball,isopoint, image sensor, character recognition, barcode scanner,microphone, and/or a speech or voice recognition system.

One or more displays 112, printers, speakers, and/or other outputdevices 216 may also be connected to the main unit 202 via the interfacecircuit 212. The display 112 may be a cathode ray tube (CRTs), a liquidcrystal display (LCD), or any other type of display. The display 112generates visual displays generated during operation of the computingdevice 102, 104. For example, the display 112 may provide a userinterface that may display one or more web pages received from acomputing device 102, 104. A user interface may typically includeprompts for human input from a user 114 including links, buttons, tabs,checkboxes, thumbnails, text fields, drop down boxes, etc., and mayprovide various outputs in response to the user inputs, such as text,still images, videos, audio, and animations.

One or more storage devices 218 may also be connected to the main unit202 via the interface circuit 212. For example, a hard drive, CD drive,DVD drive, and/or other storage devices may be connected to the mainunit 202. The storage devices 218 may store any type of data, such asimage data, video data, audio data, tag data, historical access or usagedata, statistical data, security data, etc., which may be used by thecomputing device 102, 104.

The computing device 102, 104 may also exchange data with other networkdevices 220 via a connection to communication channel 106. Networkdevices 220 may include one or more servers 226, which may be used tostore certain types of data, and particularly large volumes of datawhich may be stored in one or more data repository 222. A server 226 mayinclude any kind of data 224 including databases, programs, files,libraries, configuration data, index or tag data, historical access orusage data, statistical data, security data, etc. A server 226 may storeand operate various applications relating to receiving, transmitting,processing, and storing the large volumes of data. It should beappreciated that various configurations of one or more servers 226 maybe used to support and maintain the system 100. For example, servers 226may be operated by various different entities. Also, certain data may bestored in a client device 102 which is also stored on the server 226,either temporarily or permanently, for example in memory 208 or storagedevice 218. The network connection may be any type of networkconnection, for example, wireless connection, satellite connection,Bluetooth connection, Ethernet connection, digital subscriber line(DSL), telephone line, coaxial cable, etc.

FIG. 4 is a block diagram of an example peer group diagnosis detectionsystem 400. The peer group diagnosis detection system 400 may include apeer group diagnostic information processing system 402, a satellite406, a plurality of terminals 406, and a peer group 408. The terminaldiagnostic information processing system 402 include satellite systemprofile information 410, a profile normalizing tool 412, an operationalstatistics normalizing tool 414, and a peer group diagnosis tool 416. Itshould be appreciated that the respective diagram blocks of FIG. 4 mayrepresent one or more physical devices for ease of understanding.

A peer group diagnosis detection information processing system 402 maybe used, for example, by a company that provides satellite services,such as television, internet, telephone, etc., to customers, includinghome use customers, commercial businesses, and the like. The peer groupdiagnosis detection information processing system 402 is used to detectproblem terminals 406 by diagnosing terminals 406 within a peer group408, for example, as good, degraded, or bad. The peer group diagnosisdetection information processing system 402 may be implemented at adiagnostic center. The satellite 404 may communicate with the peer groupdiagnosis detection information processing system 402 to provide datafrom terminals 406 in the peer group 408. The satellite 404 maycommunicate with the peer group diagnosis detection informationprocessing system 402 and terminals 406, for example, as discussedabove. It should be appreciated that many terminals 406 (e.g., hundredsor thousands) may be part of a peer group 408, and likewise, manysatellites 406 and/or peer groups 408 may be included in a peer groupdiagnosis detection system 400.

The peer group diagnosis detection information processing system 402 mayinclude a database, files, or the like with satellite system profileinformation 410. The satellite system profile information typicallyincludes satellite beam profiles, satellite terminal profiles, andvarious other information regarding satellites 404 and terminals 406.The satellite system profile information may be used to determine peergroups 408. A profile normalizing tool 412 may be used to normalize abaseline profile for a peer group 408. An operational statisticsnormalizing tool 414 may be used to normalize operational statistics(e.g., signal to noise ratio, symbol rate) which may be measured atterminals 406 of the peer group 408. A peer group diagnosis tool 416 isused to diagnose terminals 406 of the peer group 408 based on thenormalized operational statistics.

FIG. 5 includes a flowchart of an example process 500 for peer groupdiagnosis detection. Although the process 500 is described withreference to the flowchart illustrated in FIG. 5, it will be appreciatedthat many other methods of performing the acts associated with theprocess 500 may be used. For example, the order of many of the blocksmay be changed, many blocks may be intermittently repeated orcontinually performed, certain blocks may be combined with other blocks,and many of the blocks described are optional or may only becontingently performed.

The example process 500 may begin when a beam profile with a pluralityof satellite beam characteristics is determined (block 502). Forexample, a beam profile for a satellite beam may include characteristicssuch as carrier frequency, beam transmission power (e.g., EffectiveIsotropic Radiated Power or EIRP), the geolocation information on thebeam including the center point or common point, the size andattenuation pattern of the beam, antenna gain, signal to noise ratio,modulation type, bit rate, tolerances, etc. It should be appreciatedthat a satellite beam is not uniform as measured from the ground, andthat a common point generally located at the center of the beam may havethe maximum downlink gain and maximum uplink sensitivity. In an exampleembodiment, satellite beam may be part of a communication systemoperating in any broadband network, for example, using the K_(a) band onthe SPACEWAY® platform.

A peer group of satellite terminals is determined (block 504). Forexample, a peer group may include all the terminals using a particularbeam and transponder. Also, for example, if a beam has a large coveragearea, a peer group may include all of the terminals located within ablock defined by a certain upper and lower latitude and longitude. Itshould be appreciated that a peer group may be determined based on avariety of other factors, for example, geological structures, weatherpatterns, other boundaries, or the like. A peer group may typicallyinclude hundreds or thousands of terminals.

Terminal profiles with terminal characteristics for the satelliteterminals in the peer group are determined (block 506). For example, foreach terminal, the terminal characteristics may include all relevanthardware specifications and the geolocation coordinates (e.g., latitudeand longitude) and/or the location from the beam center (e.g., in radialground distance or radial angle from the beam center). Hardwarespecifications may include antenna type and size, a transmission power,an antenna gain, a signal to noise ratio, a symbol rate, and any otherspecifications relevant to the configuration of a terminal.

A normalized baseline profile including normalized terminalcharacteristics for the peer group is determined (block 508). Forexample, a normalized baseline profile may be determined as a specifichardware configuration at a specific location, such as at the beamcenter. For example, the hardware configuration may be a 1 watttransmitter, a 0.74 meter dish, a symbol rate of 256, etc. It should beappreciated that the normalized baseline profile may typically representa common hardware configuration at the beam center. In an exampleembodiment, at the center of the beam, a terminal may have an expecteduplink signal to noise ratio (Es/No) of approximately 15 dB and anexpected downlink Es/No of approximately 22 dB. These expected Es/Novalues may represent an optimally configured terminal in optimalconditions. However, terminals located away from the beam center mayhave attenuated Es/No values under optimal conditions even whenoptimally configured. For example, an installing technician may set up aterminal with all the proper equipment, proper align the antenna, etc.,and if the terminal is near the edge of the satellite beam, the expectedEs/No values may be lower, and thus, more susceptible to serviceinterruptions from weather conditions or the like. Because the optimaloperational values (e.g., downlink Es/No) are different for terminalswith different hardware configurations and/or locations, a comparison ofoperational statistics between the different terminals is often oflimited value.

Operational statistics of the satellite terminals in the peer group aremeasured and received (block 510). For example, any or all uplink anddownlink statistics may be measured at the terminal, including any rawRF statistics or such as Es/No, G/T, transmission power, reception poweror other data statistics such as symbol rate, CRC error rates, latencyvalues, packet loss ratio, throughput speeds, or response times. Theoperational statistics may be continuously measured or intermittentlymeasured, for example, on a daily or hourly basis, or any other timeinterval. The measured operational statistics may then be transmitted ona regular basis to a remote location for peer group diagnosis detection,for example, hourly, daily, weekly, or on a continuous basis.

The measured operational statistics are converted into normalizedoperation statistics using the terminal profiles and the normalizedbaseline profile (block 512). For example, each of the measuredoperational statistics is adjusted to normalize each terminal to thenormalized baseline profile expected or measured operational statistics.In an example embodiment, converting the measured uplink and downlinksignal to noise ratios includes adjusting the measured values by addingan uplink normalization value and a downlink normalization valuespecific to each satellite terminal based on an antenna size, atransmission power, an antenna gain, and a distance from a satellitebeam center point. Accordingly, once the measured operational statisticsare converted into normalized operation statistics, the data representsa group of peer terminals that have the same equipment configuration andsame location. For example, if a transmitting power of a terminal isless than the transmitting power of the transmitting power of thenormalized baseline profile, a value to account for this difference maybe added to the uplink Es/No. Similarly, if a terminal is 50 miles fromthe center the satellite beam, a value accounting for this differencemay be added to the uplink and downlink Es/No. Thus, all the terminalsnormalized operation statistics should generally be the same, except forvariations due to varying cable lengths, equipment variations,measurement errors, and other various interference, which wouldtypically be relatively minor. Thus, when a terminal's normalizedoperation statistics deviate beyond the ordinary variation levels, aproblem is indicated.

Normalized peer group operational statistics are determined including amean and standard deviation of at least two of the normalizedoperational statistics (block 514). For example, the normalized peergroup operational statistics may have an uplink mean Es/No of 12 dB, adownlink mean of Es/No of 17.5 dB, with an uplink Es/No standarddeviation of 2, and a downlink Es/No standard deviation of 2.5. In anexample embodiment, a site count associated with the peer group isincluded with the normalized peer group operational statistics. Itshould be appreciated that the normalized peer group operationalstatistics may vary based on the particular communication system, thesatellite and terminals, the frequency band, the antenna types, andvarious other variables. It should be appreciated that determining peergroup operational statistics from the terminal normalized operationalstatistics may include outlier removal, or other manipulation forstatistical purposes. For example, any uplink or downlink signal tonoise ratio that has a deviation greater than 1.3 standard deviationsfrom the peer group mean may be removed from the data set to obtain arevised mean and standard deviation of the remaining terminals.Accordingly, any outliers may be removed to ensure that the normalizedpeer group operational statistics are representative of a normallyfunctioning terminal. Also, other operational statistics besides theuplink and downlink signal to noise ratio may be normalized for the peergroup in a similar fashion. For example, symbol rate, latency values,error rates, throughput speeds, signal strength, or any signal orperformance quality metric, may advantageously be used as normalizedpeer group operational statistics, alone, or in conjunction with otherstatistics.

A normalized deviation of at least two operational statistics isdetermined for each satellite terminal (block 516). For example, usingthe normalized peer group operational statistics, a normalized uplinkEs/No deviation and a normalized downlink Es/No deviation may bedetermined for each terminal in the peer group. For example, thenormalized uplink and downlink Es/No deviations of a given terminal maybe UL −0.6 σ and DL −0.8 τ. It should be appreciated that the normalizeddeviation may be expressed in units other than standard deviations (σ),for example, in decibels (dB). In this example embodiment, thenormalized deviations may be expressed, for example, as UL −1.2 dB andDL −2.0 dB instead of UL −0.6 σ and DL −0.8 σ. Other typical examples ofnormalized deviations for terminals in the example peer group may be asfollows: UL −1.5 σ and DL −0.2 σ; UL −2.1 σ and DL +0.4 σ; UL +1.2 σ andDL −0.5 σ; UL +0.3 σ and DL +1.1 σ.

The normalized deviations for each satellite terminal are compared to athreshold deviation (block 518). In an example embodiment, eachnormalized uplink and downlink deviation may be compared to a thresholdof −2.5 σ. In an example embodiment, each normalized uplink and downlinkdeviation may be compared to a threshold of −4.0 σ. It should beappreciated that a value of a threshold deviation may depend largely onthe communication system. Also, multiple threshold deviations may usedfor comparison for each normalized deviation of each terminal, or eachnormalized deviation may only be compared to a single thresholddeviation.

Each satellite terminal is diagnosed as good, degraded, or bad (block520). For example, when a terminal's normalized uplink and downlinkdeviations are above the threshold of −2.5 σ, the terminal may bediagnosed as good or OK. When either of a terminal's normalized uplinkand downlink deviations is below the threshold of −4.0 σ, the terminalmay be diagnosed as bad, and likely in need of service. When either of aterminal's normalized uplink and downlink deviations is below thethreshold of −2.5 σ, and both of a terminal's normalized uplink anddownlink deviations are above the threshold of −4.0 σ, the terminal isdiagnosed as degraded. As discussed below, FIG. 6 illustrates an examplescatter diagram illustrating such an exemplary diagnosis of terminals.It should be appreciated that the thresholds may be used todifferentiate varying degrees of problem severity, such as bydifferentiating between merely degraded terminals and bad terminals.Typically, for example, a bad terminal may provide significant serviceinterruptions while a degraded terminal may provide limited serviceinterruptions which may not even be noticeable to the customer or areduction in internet throughput speed and response times for both theuplink and downlink. However, the threshold(s) may be adjusted for eachcommunication system to provide a diagnosis as needed. For example, if aterminal is merely degraded, no action may be required, however, if thecustomer calls to complain about poor service, there is already dataconfirming that the service is not optimal and may be improved with aservice call to optimize the terminal. Also, for example, if a terminalis bad, the service provider may contact the customer and schedule anappointment to repair and optimize the terminal, which may improvecustomer relations. In an example embodiment, newly installed terminalsmay have their performance validated to ensure that installationtechnicians are properly installing terminals.

FIG. 6 includes a scatter diagram 600 illustrating an example data setof terminal deviations for peer group diagnosis detection. The scatterdiagram 600 plots the normalized deviations for the satellite terminalsof a peer group, with the x-axis representing the normalized uplinkdeviation and the y-axis representing the normalized downlink deviation,such that each data point illustrates the normalized uplink and downlinkdeviations for a satellite terminal. As discussed above, the thresholddeviations may be used to diagnose the terminals in the peer group asgood, degraded, or bad. FIG. 6 illustrates diagnosis zones 602, 604,606, which are presented on the two dimensional scatter diagram for easeof understanding. The deviation thresholds of −2.5 σ and −4.0 σ separatethe good zone 602, the degraded zone 604, and the bad zone 606.Accordingly, terminals which have normalized deviations falling in thegood zone 602 are diagnosed as good, terminals which have normalizeddeviations falling in the degraded zone 604 are diagnosed as degraded,and terminals which have normalized deviations falling in the bad zone602 are diagnosed as bad. It should be appreciated that using a scatterdiagram is not necessary to make a diagnosis, but FIG. 6 is informativein that it illustrates that the normalized deviations for the terminalsin the peer group may be advantageously compared regardless of hardwareconfiguration and location differences. Also, for example, using thenormalized deviations provides for improved performance when a rain fadeoccurs within the peer group. Generally, the entire peer group willexperience a signal degradation, so a properly working terminal will notshow any degradation relative to the peer group because the peer groupis being subjected to rain fade collectively, so there will typicallynot be any change in the normalized deviation.

FIG. 7 includes a flowchart of an example process 700 for real-timesignal validation. Although the process 700 is described with referenceto the flowchart illustrated in FIG. 7, it will be appreciated that manyother methods of performing the acts associated with the process 700 maybe used. For example, the order of many of the blocks may be changed,many blocks may be intermittently repeated or continually performed,certain blocks may be combined with other blocks, and many of the blocksdescribed are optional or may only be contingently performed.

The example process 700 may begin when a subset of terminals in a peergroup of satellite terminals is determined (block 702). For example, theexample process 500 for peer group diagnosis detection, which isdescribed above, is performed for a peer group of satellite terminals,and from that peer group, a random group of 10% of the total number ofterminals is selected. It should be appreciated that the size of a peergroup may affect the appropriate size of the subset of terminals. Forexample, a larger peer group may allow a smaller percentage subset ofterminals from the peer group to provide statistically meaningfulresults, and vice versa. A peer group may typically include 100 to 300terminals that have a common channel and frequency band in a ¼° latitudeby ¼° longitude area, and up to approximately 25 terminals in such apeer group may typically be required to provide a statisticallysignificant sample size for measurement. It should be appreciated thatthe number of terminals needed to provide a statistically significantsampling of measurements representative of the peer group will varybased on many factors, including the number of terminals in the peergroup, the geographic area of the peer group, the consistency orvariability of the measurements taken, etc. Accordingly, a subset ofterminals will most typically be 10% to 20% of the total peer group, butmay be a larger or smaller percentage, and the subset of terminals maybe 5 terminals, 25 terminals, 200 terminals, or 1,000 terminals,depending on the specific peer group.

Operational statistics of the satellite terminals in the subset ofterminals are measured and received (block 704). For example, any or alluplink and downlink statistics may be measured at each of the terminalsin the randomly selected group within the peer group. In an exampleembodiment, the uplink and downlink statistics may include any raw RFstatistics such as Es/No, G/T, transmission power, reception power orother data statistics such as symbol rate, CRC error rates, latencyvalues, packet loss ratio, throughput speeds, or response times. In anexample embodiment, more than one measurement may be taken from eachterminal to reduce measurement errors associated with each terminal. Forexample, four sets of measurements may be taken for each terminal inrelatively quick succession, such as every two seconds, and thesemeasurement results may be averaged. It should be appreciated that themeasurements may be taken more quickly or more slowly (e.g., 1 or 5seconds), and with a greater or lesser number of measurements (e.g., 2or 8 measurements). Also, for example, any terminal with erraticvariations in these measurements may be disregarded to help ensure thatthe operational statistics for the subset of terminals arerepresentative of a normally functioning terminal. In an exampleembodiment, the measurements for each terminal may be taken over alonger period of time to reduce any short term interference, forexample, every one or two minutes.

The operational statistics of each of the satellite terminals in thesubset of terminals are compared to a prior measurement of the sameoperational statistics for the subset of terminals (block 706). Forexample, an uplink Es/No and a downlink Es/No for each terminal in thesubset of terminals is compared to the uplink Es/No and the downlinkEs/No from the previous day, which can serve as a baseline measurement.For example, for a first terminal in the subset of terminals,measurements taken on Monday may include a measured uplink Es/No of 12dB and a measured downlink Es/No of 18 dB, while on Tuesday, the firstterminal measurements include a measured uplink Es/No of 10.5 dB and ameasured downlink Es/No of 16 dB. For a second terminal in the subset ofterminals, measurements taken on Monday and Tuesday may include uplinkEs/No measurements of 10 dB and 7.5 dB, and downlink Es/No measurementsof 17 dB to 13 dB, respectively.

An offset between a current measurement of an operational statistic anda prior measurement of the same operational statistic is determined foreach of the satellite terminals in the subset of terminals (block 708).For example, in the above example with measurements from Monday toTuesday, the first terminal has a decrease in the measured uplink Es/Noof 1.5 dB, and a decrease in the measured downlink Es/No of 2 dB, whilethe second terminal has a decrease in the measured uplink Es/No of 2.5dB, and a decrease in the measured downlink Es/No of 4 dB. In otherwords, each determined offset provides a differential between twodifferent measurements of the same operational statistic, for the sameterminal, at different points in time. It should be appreciated that anoffset may be a positive value (i.e., an increase over time) or anegative value (i.e., a decrease over time).

An average offset of the current measurement of the operationalstatistic and the prior measurement of the same operational statistic isdetermined for the subset of terminals (block 710). For example, thefirst and second exemplary terminals have decreases in measured uplinkEs/No of 1.5 dB and 2.5 dB, which averages to an offset of −2 dB, anddecreases in measured downlink Es/No of 2 dB and 4 dB, which averages toan offset of −3 dB. It should be appreciated that only two exemplaryterminals from the subset of terminals are provided with exemplarychanges in measured operational statistics, although typically, a subsetof terminals includes up to approximately 25 terminals, and themeasurements of these terminals are used for determining an averageoffset for the subset of terminals by determining a mean value. Further,in an example embodiment, the offsets of the subset of terminals may besubject to outlier removal or other manipulation for statisticalpurposes. For example, for a given operational statistic, any offsetthat has a deviation greater than 1.3 standard deviations from the meanoffset of the subset of terminals may be removed from the data set toobtain a revised offset of the remaining terminals in the subset ofterminals. Accordingly, any outliers may be removed to ensure that theaverage offset for the subset of terminals is representative of anormally functioning terminal.

The average offset for the subset of terminals is merged with previouslydetermined peer group operational statistics (block 712). For example,as explained above with regard to block 514, previously determinednormalized peer group operational statistics may include an uplink meanEs/No of 12 dB, a downlink mean Es/No of 17.5 dB, which are merged withthe average offsets of −2 dB uplink Es/No and −3 dB downlink Es/No,providing for updated deviations values. In an example embodiment, atable stores the currently determined average offsets for uplink Es/Noand downlink Es/No, a previously determined uplink Es/No mean anddownlink Es/No mean for the peer group, and a previously determineduplink Es/No standard deviation value and downlink Es/No standarddeviation value for the peer group. In an example embodiment, theaverage offsets may be merged with the previously determined normalizedpeer group operational statistics by adding the average offsets to, forexample, the previously determined uplink mean Es/No of 12 dB anddownlink mean Es/No of 17.5 dB to provide an updated uplink mean Es/Noof 10 dB and an updated downlink mean Es/No of 14.5 dB. In an exampleembodiment, as explained above with regard to block 514, previouslydetermined normalized peer group operational statistics may include anuplink Es/No standard deviation of 2 dB, and a downlink Es/No standarddeviation of 2.5 dB. As explained with regard to block 518, a thresholddeviation of −2.5 σ for both uplink Es/No and downlink Es/No, is usedfor comparison to measured statistics of terminals in the peer group.For example, the threshold deviation for uplink Es/No of −2.5 σ can beoffset by the average offset of −2 dB, or −1 σ for a standard deviationof −2 dB, to an updated threshold deviation for uplink Es/No of −3.5 σ.Likewise, the threshold deviation for downlink Es/No of −2.5 σ can beoffset by the average offset of −3 dB, or −1.2 σ for a standarddeviation of −2.5 dB, to an updated threshold deviation for downlinkEs/No of −3.7 σ. It should be appreciated that threshold deviations maybe expressed in a variety of ways, including standard deviations (σ) ordecibels (dB). For example, updated threshold deviations may beexpressed in decibels, such as an uplink Es/No of 5 dB and a downlinkEs/No of 8.25 dB. These exemplary average offsets based on themeasurements of operational statistics from the subset of terminals mayindicate that the signal quality for the peer group has deteriorated,for example, due to weather conditions such as rain.

It should be appreciated that additional and/or different operationalstatistics that those described by way of example above may be used, forexample, a reception power, a transmission power, an error rate, and alatency value. In an example embodiment, updated deviation values may beprovided in a table which is regularly updated (e.g., a database table),and may be presented as average offset values, updated means, updatedstandard deviations, or the like. It should also be appreciated that thepreviously determined normalized peer group operational statisticsand/or the average offsets may be manipulated in a variety of ways toprovide updated deviation values for comparison and/or manipulation ofcurrent measurements of operational statistics for terminals in the peergroup. In an example embodiment, previously determined peer groupoperational statistics that are merged with an average offset may havebeen previously merged with an average offset at a previous time,providing for operational statistics that may be incrementally updatedwith average offsets over time.

A signal validation of a terminal is performed using an updateddeviation value (block 714). For example, a newly installed terminalprovides measurement data of 6 dB uplink Es/No and 9 dB downlink Es/No,which may normally not be considered a good installation, but arainstorm is currently occurring. The previously determined uplink Es/Nomean of 12 dB and downlink Es/No mean of 17.5 dB, and the currentlydetermined average offsets of −2 dB uplink Es/No and −3 dB downlinkEs/No, are both subtracted from the current measurements of 6 dB uplinkEs/No and 9 dB downlink Es/No, resulting in values of −4 dB and −5.5 dB,respectively. These values may be converted into standard deviations bydividing by the uplink Es/No standard deviation of 2 dB, and thedownlink Es/No standard deviation of 2.5 dB, discussed above in block712, resulting in updated uplink and downlink deviation values for thenewly installed terminal of −2 σ and −2.2 σ. Upon comparison to therespective threshold deviations of −2.5 σ and −2.5 σ, the newlyinstalled terminal is validated using the updated deviation valuesbecause −2 σ and −2.2 σ are above the threshold deviations of −2.5 σ and−2.5 σ. In another example embodiment, updated deviation values in theform of updated threshold deviations provide a validation of a newlyinstalled terminal with a measured uplink Es/No of 5.2 dB and a measureddownlink Es/No of 8.4 dB (e.g., diagnosed as good), even though thesemeasured values might typically indicate that there is a problem withthe newly installed terminal (e.g., diagnosed as degraded). The averageoffsets of −2 dB and −3 dB, which have been determined using currentdata from the subset of terminals, provides for the use of updatedthreshold deviations that take into account a rainstorm that iscurrently deteriorating the uplink and downlink signal quality of theterminals in the peer group. Moreover, for example, the terminal with ameasured uplink Es/No of 5.2 dB and a measured downlink Es/No of 8.4 dBshould have approximately a uplink Es/No of 7.2 dB and a measureddownlink Es/No of 11.4 dB if the current rainstorm were not impactingthe signal quality for that terminal, and accordingly, provide a levelof signal quality that is acceptable for a terminal performancevalidation at the time of installation. However, if the average offsetsdetermined using current data from the subset of terminals were notmerged with the previously determined peer group operational statistics,the terminal installation could not be validated due the rainstormaffecting the signal quality at the time of installation. It should beappreciated that the measured operational statistics of each terminalmay be normalized, for example, as explained above with regard to block512, prior to any comparison to the updated threshold deviations. Also,in an example embodiment, the measured operational statistics may bestored in a format which generally requires a minimal amount ofcomputational processing for performing relevant statisticalcomparisons.

Signal validation, or terminal performance validation, may occur uponrequest or at regularly scheduled intervals. Also, determining andmerging average offsets with peer group operational statistics may occurat regularly scheduled intervals or upon request. For example, uponinstalling a new terminal, a real-time signal validation may occur usingmeasured operational statistics, which are obtained following receivinga request, or which have been recently obtained (e.g., within the lasthour). In an example embodiment, a customer complaint may trigger arequest for a real-time signal validation of the relevant terminal. Inan example embodiment, the example process 700 may occur with increasedfrequency to provide more frequently updated deviation values uponreceiving an indication of severe weather in a specific weather impactedcell of terminals of a peer group. It should be appreciated that anaverage offset may be determined and merged with previously determinedpeer group operational statistics to provide for updated deviationvalues, but that no signal validation of any specific terminal must beperformed using the updated peer group operational statistics, forexample, if no terminal installations are performed and/or no customercomplaints are received before a new subset of terminals provides a newaverage offset. In an example embodiment, new average offsets aredetermined at least once every hour (e.g., every 30 minutes), and theresulting updated deviation values are stored in a table for reference.The frequency of determining an average offset may depend on a varietyof factors, such as the geographic size of a peer group. For example,the geographic size relates to the amount of time it takes a weatherfront to move into the area of the peer group, so a half hour or onehour sampling frequency may be appropriate if bad weather is a primarysource of interference. If a source of interference has a quickervariability, then the sampling frequency would typically need to behigher (e.g., every 15 minutes), whereas a system having a slowlychanging source of interference may have a lower sampling frequency fordetermining average offsets (e.g., every 6 hours). In an exampleembodiment, a primary source of interference may be network traffic atpeak usage times. In an example embodiment, the subset of terminals maybe determined by randomly selecting a group of terminals located withina certain proximity of a target terminal (e.g., within a one mile radiusof a new installation). Also, in an example embodiment, a peer group maybe divided in multiple different areas, with each area having acorresponding subset of terminals (e.g., quadrants of a peer group).

Accordingly, the presently disclosed methods and systems mayadvantageously detect a problem before a customer notices any problem ordecline in service, thus improving customer service relations. Forexample, a customer may never need to call a customer service line torequest that a problem be diagnosed because, before any decline ininternet speed or television reception quality occurs, the problem isdetected and diagnosed by the peer group diagnosis detection method andsystem. Further, the presently disclosed methods and systems mayvalidate good installations of satellite terminals using real-time data.The use of real-time data to validate installations of satelliteterminals may provide a service technician with real-time confirmationthat an installation is good or, alternatively, notify the technician inreal-time that an installation is bad so it can be corrected before thetechnician leaves the installation site. Accordingly, real-time signalvalidation may greatly minimize repair visits due to improperinstallations. It should be appreciated that, for example, the rate ofunnecessary repair visits may be reduced to less than 0.01% of allrepair visits. Accordingly, a great reduction in costs and improvementin customer service may be achieved using the presently disclosedreal-time signal validation method and system.

For exemplary purposes, the present disclosure discusses a variousexamples relating to a satellite communication system. However, itshould be appreciated that the disclosed system, methods, and apparatusmay be advantageously used in various different types of communicationsystems including, for example, systems that do not use satellites(e.g., a terrestrial point to point communication system).

It will be appreciated that all of the disclosed methods and proceduresdescribed herein can be implemented using one or more computer programsor components. These components may be provided as a series of computerinstructions on any conventional computer readable medium, includingRAM, ROM, flash memory, magnetic or optical disks, optical memory, orother storage media. The instructions may be configured to be executedby a processor, which when executing the series of computer instructionsperforms or facilitates the performance of all or part of the disclosedmethods and procedures.

It should be understood that various changes and modifications to theexample embodiments described herein will be apparent to those skilledin the art. Such changes and modifications can be made without departingfrom the spirit and scope of the present subject matter and withoutdiminishing its intended advantages. It is therefore intended that suchchanges and modifications be covered by the appended claims. Also, itshould be appreciated that the features of the dependent claims may beembodied in the systems, methods, and apparatus of each of theindependent claims.

The invention is claimed as follows:
 1. A method comprising: determininga subset of terminals in a peer group of satellite terminals; receivinga first measurement of an operational statistic of the satelliteterminals in the subset of terminals; comparing the first measurement ofthe operational statistic of each of the satellite terminals in thesubset of terminals to a prior second measurement of the sameoperational statistic for each of the satellite terminals in the subsetof terminals; determining an offset between the first measurement of theoperational statistic and the prior second measurement of the sameoperational statistic for each of the satellite terminals in the subsetof terminals; updating a previously determined peer group operationalstatistic based on determined offsets; and performing a signalvalidation of a terminal using an updated deviation value.
 2. The methodof claim 1, wherein the subset of terminals includes a number ofsatellite terminals in a range of 10% to 25% of the peer group ofsatellite terminals.
 3. The method of claim 1, wherein the subset ofterminals is determined by randomly selecting a predetermined number ofterminals from the peer group.
 4. The method of claim 1, wherein theoperational statistic is one of a reception power, a transmission power,a signal to noise ratio, an error rate, and a latency value.
 5. Themethod of claim 1, wherein the operational statistic is one of an uplinksignal to noise ratio and a downlink signal to noise ratio.
 6. Themethod of claim 1, wherein the operational statistic of the satelliteterminals in the subset of terminals is measured on a regular timeinterval.
 7. The method of claim 1, wherein a plurality of samples aremeasured at each terminal in the subset of terminals, and the pluralityof samples are averaged to determine the offset for each terminal in thesubset of terminals.
 8. The method of claim 1, wherein updated deviationvalues including at least one of average offset values, updated meanvalues, and updated threshold deviation values, are stored in a table tobe referenced for terminal performance validation.
 9. The method ofclaim 1, wherein each satellite terminal of the subset of terminals arelocated within a certain proximity of a target terminal.
 10. The methodof claim 1, wherein a plurality of subsets of terminals each provide anaverage offset for a plurality of different areas of the peer group. 11.The method of claim 1, wherein updating the previously determined peergroup operational statistic includes: determining an average offset ofthe first measurement of the operational statistic and the prior secondmeasurement of the same operational statistic for the subset ofterminals; and merging the average offset for the subset of terminalswith the previously determined peer group operational statistic.
 12. Asystem comprising: a computer readable medium storing satellite profileinformation; and at least one processing device operably coupled to thecomputer readable medium, the at least one processing device executinginstructions to: determine a subset of terminals in a peer group ofsatellite terminals; receive a first measurement of an operationalstatistic of the satellite terminals in the subset of terminals; comparethe first measurement of the operational statistic of each of thesatellite terminals in the subset of terminals to a prior secondmeasurement of the same operational statistic for each of the satelliteterminals in the subset of terminals; determine an offset between thefirst measurement of the operational statistic and the prior secondmeasurement of the same operational statistic for each of the satelliteterminals in the subset of terminals; updating a previously determinedpeer group operational statistic based on determined offsets; andperform a signal validation of a terminal using an updated deviationvalue.
 13. The system of claim 12, wherein the subset of terminalsincludes a number of satellite terminals in a range of 10% to 25% of thepeer group of satellite terminals.
 14. The system of claim 12, whereinthe subset of terminals is determined by randomly selecting apredetermined number of terminals from the peer group.
 15. The system ofclaim 12, wherein the operational statistic is one of a reception power,a transmission power, a signal to noise ratio, an error rate, and alatency value.
 16. The system of claim 12, wherein the operationalstatistic is one of an uplink signal to noise ratio and a downlinksignal to noise ratio.
 17. The system of claim 12, wherein theoperational statistic of the satellite terminals in the subset ofterminals is measured on a regular time interval.
 18. The system ofclaim 12, wherein a plurality of samples are measured at each terminalin the subset of terminals, and the plurality of samples are averaged todetermine the offset for each terminal in the subset of terminals. 19.The system of claim 12, wherein updated deviation values including atleast one of average offset values, updated mean values, and updatedthreshold deviation values, are stored in a table to be referenced forterminal performance validation.
 20. The system of claim 12, whereineach satellite terminal of the subset of terminals are located within acertain proximity of a target terminal.
 21. The system of claim 12,wherein a plurality of subsets of terminals each provide an averageoffset for a plurality of different areas of the peer group.
 22. Thesystem of claim 12, wherein updating the previously determined peergroup operational statistic includes: determining an average offset ofthe first measurement of the operational statistic and the prior secondmeasurement of the same operational statistic for the subset ofterminals; and merging the average offset for the subset of terminalswith the previously determined peer group operational statistic.